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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250904T100000
DTEND;TZID=Asia/Singapore:20250904T113000
DTSTAMP:20260416T155709
CREATED:20250901T085532Z
LAST-MODIFIED:20250901T085532Z
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SUMMARY:DAO-ISEM-IORA Seminar Series: Nur Sunar
DESCRIPTION:Name of Speaker\n Nur Sunar\n\n\nSchedule\n 4 September 2025\, 10am – 11.30am\n\n\nVenue\n HSS 3 – 2 (Hon Sui Sen Memorial Library\, level 3 Seminar Room)\n\n\nLink to Register\nhttps://nus-sg.zoom.us/meeting/register/lZ34DiDOTh6rI4zJehKPIQ\n\n\nTitle\nDesigning Renewable Power Purchase Agreements: Impact on Green Energy Investment\n\n\nAbstract\nThis paper studies a long-term power purchase agreement (PPA) between a firm and a new renewable energy generator. The firm must dynamically satisfy uncertain electricity demand beyond its existing energy sources\, while wholesale electricity prices evolve stochastically over time. Upon signing a PPA\, a new renewable facility becomes operational\, and the firm owns its output for the contract duration. The new facility’s capacity is determined based on PPA terms. The firm dynamically chooses when to initiate the PPA and how much to pay to maximize its expected total discounted benefit. We show that the firm’s optimal timing follows a (time-dependent) threshold policy. Our results offer key insights for policymakers and renewable energy developers. We find that\, contrary to common wisdom\, reducing investment costs for renewable technologies can lead to smaller renewable capacity\, output\, and emissions savings when projects are developed under PPAs. This finding calls for caution in applying investment tax credits in such contexts. We also show that total renewable energy generation and emissions savings may decrease with higher site productivity. Therefore\, restricting renewable facility development to most productive sites might be counterproductive under PPAs. We establish the robustness of our findings across a broad range of practical scenarios. \n(joint work with Zuguang Gao and John R. Birge)\n\n\nAbout the Speaker\nNur Sunar is an Associate Professor of Operations and Sarah Graham Kenan Scholar at the Kenan-Flagler Business School of the UNC at Chapel Hill. She received her Ph.D. from Stanford Graduate School of Business with a thesis titled “Management Problems in Energy and Sustainability.” Her current research interest is to study innovative business models\, technologies\, and policies\, with a focus on sustainability\, energy\, and digital platforms. A key theme of her recent research is doing good with management science. \nDr. Sunar is particularly interested in innovative business models and novel challenges related to renewable energy technologies (e.g.\, rooftop solar panels\, large-scale renewable energy technologies\, online solar marketplaces)\, sustainability practices of companies/organizations (e.g.\, voluntary carbon offsetting) and smart city technologies (e.g.\, the Internet of Things\, smart meters\, electric vehicles\, and residential batteries). She is also passionate about innovative business solutions for inclusive health. \nFor more information\, please see https://sites.google.com/view/nur-sunar/home
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-nur-sunar/
CATEGORIES:IORA Seminar Series
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BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250905T100000
DTEND;TZID=Asia/Singapore:20250905T113000
DTSTAMP:20260416T155709
CREATED:20250901T085409Z
LAST-MODIFIED:20250901T085409Z
UID:27041-1757066400-1757071800@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Victor Martínez de Albéniz
DESCRIPTION:Name of Speaker\nVictor Martínez de Albéniz\n\n\nSchedule\n5 September 2025\, 10am – 11.30am\n\n\nVenue \nHSS 4 – 7 (Hon Sui Sen Memorial Library\, level 4 Seminar Room)\n\n\nLink to Register \n \nhttps://nus-sg.zoom.us/meeting/register/kZSaUc7SR_GuEKdg2LC_SA\n\n\nTitle\nDigital Nudges at the Van Gogh Museum Increase Engagement\, Pace Visitors\, and Reduce Congestion\n\n\nAbstract\nDigital nudges have the potential to enrich experiential services\, but little is known about how they affect behaviors in the field. From 2022 to 2024\, we run field experiments at the Van Gogh Museum\, testing the effect of interventions on the multimedia tour on visitor content consumption and movements. We find that providing that providing a highlight selection with a simple information architecture can increase consumption\, coverage of the collection\, without requiring more visit duration\, thereby containing museum fatigue. Furthermore\, faster visitor flows reduce congestion\, creating a positive externality on others. Thus\, well-designed digital nudges can produce more effective visits\, that improve both consumer and service provider outcomes.\n\n\nAbout the Speaker\nVictor Martínez de Albéniz is a Full Professor in the Operations\, Information and Technology Department at IESE Business School. He joined IESE in 2004 after earning a PhD from the Operations Research Center at the Massachusetts Institute of Technology (MIT) and an engineering degree from École Polytechnique in France. \nHis research spans a broad spectrum of Operations Management. He began his career working on supply chain management\, optimizing inventory and purchasing systems to combine low costs with flexibility and innovation. He then moved into the retail sector\, developing fashion trend forecasts\, leveraging big data to respond to demand shocks\, and optimizing the in-store customer experience. More recently\, he has applied his expertise to improving education systems. \nFor more information\, please see https://blog.iese.edu/martinezdealbeniz/
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-victor-martinez-de-albeniz/
CATEGORIES:IORA Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Singapore:20250917T100000
DTEND;TZID=Asia/Singapore:20250917T113000
DTSTAMP:20260416T155709
CREATED:20250908T023547Z
LAST-MODIFIED:20250908T023547Z
UID:27074-1758103200-1758108600@iora.nus.edu.sg
SUMMARY:DAO-ISEM-IORA Seminar Series: Chen Ningyuan
DESCRIPTION:Name of Speaker\n\n\n\nChen Ningyuan\n\n\n\n\n\nSchedule\n\n\n\n17 September 2025\, 10am – 11.30am\n\n\n\n\n\nVenue\n\n\n\nBIZ1 – 0202\n\n\n\n\n\nLink to Register\n(Via Zoom)\n\n\nhttps://nus-sg.zoom.us/meeting/register/n1RflnWjRwyd5RSu7W6rag\n\n\n\n\nTitle\n\n\nPost-Estimation Adjustments in Data-Driven Decision-Making with Applications in Pricing\n\n\n\n\nAbstract\n\n\nThe predict-then-optimize (PTO) framework is a standard approach in data-driven decision-making\, where a decision-maker first estimates an unknown parameter from historical data and then uses this estimate to solve an optimization problem. While widely used for its simplicity and modularity\, PTO can lead to suboptimal decisions because the estimation step does not account for the structure of the downstream optimization problem. We study a class of problems where the objective function\, evaluated at the PTO decision\, is asymmetric with respect to estimation errors. This asymmetry causes the expected outcome to be systematically degraded by noise in the parameter estimate\, as the penalty for underestimation differs from that of overestimation. To address this\, we develop a data-driven post-estimation adjustment that improves decision quality while preserving the practicality and modularity of PTO. We show that when the objective function satisfies a particular curvature condition\, based on the ratio of its third and second derivatives\, the adjustment simplifies to a closed-form expression. This condition holds for a broad range of pricing problems\, including those with linear\, log-linear\, and power-law demand models. Under this condition\, we establish theoretical guarantees that our adjustment uniformly and asymptotically outperforms standard PTO\, and we precisely characterize the resulting improvement. Additionally\, we extend our framework to multi-parameter optimization settings. Numerical pricing experiments demonstrate that our method consistently improves revenue\, particularly in small-sample regimes where estimation uncertainty is most pronounced. This makes our approach especially well-suited for pricing new products or in settings with limited historical price variation.\n\n\n\n\nAbout the Speaker\n\n\nDr. Ningyuan Chen is currently an associate professor at the Department of Management at the University of Toronto\, Mississauga and at the Rotman School of Management\, University of Toronto. Before joining the University of Toronto\, he was an assistant professor at the Hong Kong University of Science and Technology. Prior to that\, he was a postdoctoral fellow at the Yale School of Management. He received his Ph.D. from the Industrial Engineering and Operations Research (IEOR) department at Columbia University in 2015. His studies have been published in Management Science\, Operations Research\, Annals of Statistics\, NeurIPS and other journals and proceedings. His research is supported by the UGC of Hong Kong and the Discovery Grants Program of Canada. He is the recipient of the Roger Martin Award for Excellence in Research and the IMI Research Award.
URL:https://iora.nus.edu.sg/events/dao-isem-iora-seminar-series-chen-ningyuan/
CATEGORIES:IORA Seminar Series
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